The aim of the following analysis is to determine if teams that take shots from Zone 2 score more points than teams that do not.
Before analysing the data the following packages will need to be loaded;
here - constructs a path to the projects data file
tidyverse - a set of packages designed to work in together, packages needed within tidyverse include dtplyr and ggplot2
knitr - provides a general purpose tool for generating reports
plotly - creates interactive web graphics in conjunction with ggplot2
viridis - colours graphs in a readable format for color blind individuals
# Load required packages
library(here)
library(tidyverse)
library(knitr)
library(plotly)
library(viridis)
library(flexdashboard)
Load the data by using the read.csv function and the here package.
# Load in the data
Dataset3_Assessment3 <- read.csv(here("Data/Dataset3_Assessment3.csv"))
SummaryData_All <- Dataset3_Assessment3 %>%
group_by(Team, Statistic) %>%
summarise(Min = min(Total),
Max = max(Total),
Mean = mean(Total),
SD = sd(Total),
Sum = sum(Total))
SummaryData_attempt_from_zone2 <-
filter(SummaryData_All, Statistic == "attempt_from_zone2")
PlotAttempts <- ggplot(SummaryData_attempt_from_zone2, aes(x = Statistic, y = Sum)) +
geom_jitter(aes(colour = Team)) +
scale_colour_viridis_d() +
geom_boxplot(alpha = 0.3) +
xlab("Attempts from Zone 2") +
ggtitle("Figure 1")+
theme_classic()
#make the plot interactive
ggplotly(PlotAttempts)